BLUF:
* To determine whether AI is ‘improving exponentially’, ‘hitting the wall’, or any other claim which involves a quantity or magnitude (e.g. ‘This model was a big leap/small increment’). We need a good y-axis: an interval scale of AI capability which means +1 unit always represents the same degree of ‘how much better’, in the same way +1 degree Celsius is always the same amount of ‘how much hotter’.
* Yet there is no good y-axis for AI capability. All our...
Summary
* The animal welfare movement has already seen an influx in funding and should prepare for the possibility of more.
* The EA Animal Welfare Fund is encouraging those working in animal advocacy to actively set aside time and resources now to concretely plan for scaling sustainably, and we’ll support you in doing that.
* We’re requesting advocates set concrete ambitious goals and submit plans t...
Public service announcement
1. Applications are now open for our first ever round of the Charity Entrepreneurship Incubation Program dedicated exclusively to animal welfare. Learn more about what’s different this round here and apply...
This is too tangential from the forecasting discussion to justify being a comment there so I'm putting it here:
Forecasting makes no sense as a cause area, because cause areas are problems, something like "people lack resources/basic healthcare/etc.", "we might be building superintelligent AI and we have no idea what we're doing". Forecasting is more like a tool. People use forecasting to address AI, global poverty, and all sorts of more general problems, including ones that aren't major EA focuses.
For instance, we could treat vaccines as a cause area. All the funding to some AI-x-biosecurity people, GAVI campaigns for existing vaccines, and people working on bird flu vaccines could be treated like they're doing the same thing. And then we could argue about whether vaccines meet the funding bar. But that would be a pretty pointless argument, when really all those projects are trying to do different things with similar tools.
So I'd rather judge the AI forecasting by AI standards, the general-purpose forecasting by metascience standards, and the global development forecasting by global development standards, rather than trying to lump them in as a single entity. That being said, I do side with the view that there's too much money and enthusiasm being spent on forecasting, but it's a weakly held view, and that doesn't mean that every forecasting project isn't worth being funded, or even that they're all equally inflated.